This invention relates to a method and an apparatus for validating articles of currency, particularly coins.
It is known to validate coins by monitoring the outputs of a plurality of sensors each responsive, to different characteristics of the coin, and determining that a coin is valid only if all the sensors produce outputs indicative of a particular coin denomination. Often, this is achieved by deriving from the sensors particular values indicative of specific parts of the sensor signal. For example, an electromagnetic sensor may form part of an oscillator, and the amplitude of the oscillations may vary as a coin passes a sensor. In some arrangements, the peak value of the amplitude variation is used as a parameter indicative of certain coin characteristics, and this value is compared with respective ranges each associated with a different coin denomination. Sometimes other features of the output waveform are examined. Often coins travel past sensors under the force of gravity, e.g. by rolling, or in free fall, while the measurements are made. Because the coin position at any given instant is indeterminate, the sensor waveforms are monitored to observe when the particular feature of interest occurs.
It would be desirable to provide an improved validation technique which derives further information from the outputs of the sensors.
Some coins are formed of a composite of two or more materials, and have an inner disc surrounded by an outer ring, the disc having a different metallic content from that of the outer ring. Often, each of the inner disc and the outer ring is of an homogeneous metal, but it would be possible for one or the other or both to be formed of two or more metals. For example, the inner disc may be formed of a core material with outer cladding of a different material. Coins which have an inner disc of different material content to that of a surrounding ring will be referred to herein as xe2x80x9cbicolourxe2x80x9d coins. (This expression is intended to encompass the possibility of any number of rings of different materials.) WO-A-93/22747 describes a technique for validating bicolour coins in which two small sensors are located at positions spaced along a coin ramp so that they are passed in succession by a coin rolling along the ramp. A sensor circuit is responsive to the difference between the outputs. This permits easy recognition of bicolour coins, because a significant differential output is produced when one sensor is located in proximity to the coin ring, and the other is located in proximity to the inner disk. However, this arrangement requires a special sensor configuration.
It would be desirable to provide an improved validation technique which is particularly, but not exclusively, suitable for bicolour coins.
It would also be desirable to provide a novel and useful technique for validating banknotes and the like.
According to a further aspect of the invention, articles of currency are validated by taking sensor signals which represent different sensed characteristics of a currency article being scanned, and determining whether there is a predetermined relationship between the patterns of variation of the signals.
According to a still further aspect, currency articles are validated by determining whether a predetermined relationship is maintained between at least three varying signals each derived from a sensor scanning the article.
According to a yet further aspect, currency articles are validated by determining whether successive changing values of a signal derived from a sensor bear a predetermined relationship with successive changing values of a different sensor signal.
The various sensor signals may be derived from respective sensors, although it is also possible for some or all to be derived from the same sensor.
The techniques of the present invention thus enable, in a coin validator, the validation operation to take into account parts of the sensor output waveforms which are traditionally ignored, these parts containing useful information regarding the coin, and being of value in the authentication of the coin despite the fact that the times at which they occur may be indeterminate.
In a currency validator according to a preferred embodiment, samples of the signal from one sensor are combined in a predetermined manner with corresponding samples from another sensor. The corresponding samples are preferably samples which occur at substantially the same time. The samples can be combined in any of a number of different ways, but preferably the result of the combination is the production of an output value which indicates whether or not the relationship between the varying sensor signals departs from a predetermined relationship expected for a currency article of a particular denomination. (To check for different denominations, the validator can check to determine whether different predetermined relationships are met.) Preferably, the samples are combined by summing weighted values of the samples and then, preferably, applying the sum to a non-linear function. Preferably, the samples from one of the sensors, or more preferably two or more of the sensors, are combined in a predetermined way in order to produce an output value which varies according to an expected variation in the signal from a further sensor, and means are provided to check whether the output value and the signal from the further sensor match.
The summing of the weighted samples, and the application of the result to a non-linear function, can be performed a number of times, using different weights, with the outputs of the non-linear functions also being combined in a weighted manner.
To derive the weighting factors, a neural network can be trained in a per se known manner, e.g. using back propagation.
The neural network may be embodied as a suitably-programmed microprocessor. Alternatively, the neural network may be embodied as hardware, responsive either to discrete samples of the sensor signals or to the continuous outputs.
While neural networks provide a rapid method of generating an algorithm to process the data algorithms could obviously be developed by other methods to provide discrimination between numerical representations of the waveforms. Analysis would lead to an understanding of the relationships between the sensor outputs and the known form of the currency article giving rise to the signal. The outputs could be analysed in combination to discover deeper interrelationships. Non linearities might be accommodated by use of power laws, logarithms, trigonometrical or other functions. Regression techniques could be employed, for example, with polynomials to develop a model which ultimately relates the waveforms. These approaches would work, but use of a neural network is preferred because it leads to a fast and sufficiently effective result which is simple to incorporate in a product.
A significant advantage of the arrangement described above is that validation of currency articles can take advantage of non-obvious correlations between parts of the sensor signals which are not normally taken into account, and particularly, correlations between the changing parts of the signals.
A further advantage of the arrangement described above is that the determination of whether the predetermined relationship exists between the varying signals is not dependent on the speed of the currency article relative to the sensors. Any delays in the time at which particular sensor output values are reached due to a slow-moving article will be matched by delays in the signals from the other sensors. However, in this arrangement, it is desirable for the sensors to be positioned such that for each sensor there is a period in which its output and that of another sensor are simultaneously influenced by an article being tested (although of course there may be other sensors whose outputs are disregarded for the purpose of determining whether the predetermined relationship is maintained). On the other hand, it may be desirable for at least one sensor to be arranged such that it is not influenced at the same time as any other sensor, when at least one type of genuine article is being tested, so that if it is found to be influenced while one or more other sensors are also influenced, this is an indication that the article being tested is not an article of that type.
In an alternative embodiment, instead of combining substantially contemporaneous samples, the output from a sensor during one period can be compared with the output for a different sensor during a different period. This then avoids any restrictions on the relative placement of the sensors. Also, taking electromagnetic coin sensors as an example, this alternative would enable the comparison of the parts of the sensor outputs which contain the most important information, which can often be the centre parts of the waveforms, without placing any particular restriction on the relative positioning of the sensors. However, in this case the determined relationship between the sensor signals would be influenced by variations in the speed of the article. To compensate for this, the validator can be arranged to compare samples from one sensor output with delayed samples from another sensor output, the delay period being varied in accordance with the sensed movement (e.g. position, speed and/or acceleration) of the article. In an alternative embodiment a controller controls both the movement of the article and the sampling of the sensor signal.
Preferably, further checks are carried out on the sensor outputs to determine whether they meet other acceptance criteria, in a per se known manner. For example, with electromagnetic coin sensors, the peak levels can be compared with expected ranges for respective denominations. Instead of using the peak levels directly, it is possible to normalise by using the relationship (e.g. the difference or the ratio) between the peak levels and the values of the sensor signals with no coin present. The peak values from different sensors can be combined in a predetermined manner before applying acceptance criteria (e.g. as shown in EP-A496 754).